Index Catalog // ScholarsArchive@OSU

A Security Analysis of the Signal Protocol’s Group Messaging Capabilities in Comparison to Direct Messaging

Creator:: Jansen, Matthew L.
Abstract:: Signal is a multimedia messaging application developed by OpenWhisper Systems in 2015 which allows its users to communicate securely between one another through the use of a complex encryption scheme. The set of algorithms used in combination to provide the services of the Signal application to their users is called...
Resource Type:: Honors College Thesis
Full Text:: Capabilities in Comparison to Direct Messaging by Matthew Jansen A THESIS

A collaborative filtering algorithm and evaluation metric that accurately model the user experience

Creator:: McLaughlin, Matthew
Abstract:: "Collaborative filtering algorithms’ performances have been evaluated using a variety of metrics. These metrics, such as Mean Absolute Error and Precision, have often ignored recommendations for which they do not have data. Ignoring these recommendations has provided numbers which do not accurately represent the user experience. Qualitatively we have seen...
Resource Type:: Capstone Project
Full Text:: …………………...…………………………………... 5 Eq. 7 …………………...…………………………………... 12 1 A Collaborative Filtering Algorithm and Evaluation

A Study of Temporal Convolutional Neural Networks for Music Language Modeling as Applied to Automatic Music Transcription

Creator:: Meyn, Matthew
Abstract:: Automatic music transcription (AMT) is the task, given an acoustic representation of music, to recover a symbolic notation of the written notes expressed by the sound. Transcribing music with multiple notes sounding simultaneously is difficult for both humans and machines. Much existing work on AMT has focused on suitable acoustic...
Resource Type:: Capstone Project
Full Text:: Modeling as Applied to Automatic Music Transcription by Matthew Meyn A PROJECT REPORT submitted to

Counterfactual States for Atari Agents via Generative Deep Learning

Creator:: Olson, Matthew L.
Abstract:: Although deep reinforcement learning agents have produced impressive results in many domains, their decision making is difficult to explain to humans. To address this problem, past work has mainly focused on explaining why an action was chosen in a given state. A different type of explanation that is useful is...
Resource Type:: Masters Thesis
Full Text:: gain a better under- standing of an agent’s decision making process. c©Copyright by Matthew Lyle

3D Voronoi Subdivision for Simulating Destructible and Granular Materials

Creator:: Clothier, Matthew M.
Abstract:: In many traditional computer graphics applications, rendered scenes typically utilize 3D meshes to represent objects within an environment. As the demand to further improve the realism of graphics applications increases, such as for movies and games, it is becoming more important to represent the inner volumes of object meshes. In...
Resource Type:: Dissertation
Full Text:: Simulating Destructible and Granular Materials by Matthew Clothier A

Characterizing and Addressing Dataset Shift with Deep Learning

Creator:: Olson, Matthew L.
Abstract:: This dissertation delves into understanding, characterizing, and addressing dataset shift in deep learning, a pervasive issue for deployed machine learning systems. Integral aspects of the problem are examined: We start with the use of counterfactual explanations in order to characterize the behavior of deep reinforcement learning agents in visual input...
Resource Type:: Dissertation
Full Text:: with Deep Learning by Matthew L. Olson A DISSERTATION submitted to Oregon State University in

The Implementation of Passive RFID Tags to Sample Volumetric Water Content for an Autonomous Irrigation System

Creator:: Guo, Matthew D.
Abstract:: The agricultural industry in the Western United States continues to possess issues of overwatering, accounting for over 80% of consumed water per year in the country. While technologies such as satellite imaging and sensor networks have slowly improved irrigation Best Management Practices to reduce superfluous water consumption, limitations associated with...
Resource Type:: Honors College Thesis
Full Text:: Volumetric Water Content for an Autonomous Irrigation System by Matthew Guo

Analysis of Convolutional Neural Network Image Pre-processing Methods

Creator:: Jacobsen, Matthew
Abstract:: Oceanic plankton have both a large impact on our oceans health and atmo- spheric balance of Co2. The overall health of planktonic life is determined by many physical, chemical, and ecological factors, that drive taxonomic abundances and the relative amount of non-living biomass called detritus. Recent advances in microscopic imaging...
Resource Type:: Honors College Thesis
Full Text:: Matthew Jacobsen A THESIS submitted to Oregon State University Honors College in partial fulfillment

Machine Learning for Precision Medicine: Application to Cancer Chemotherapy Response Prediction and Wound Healing Status Assessment

Creator:: Wei, Qi
Abstract:: Ph.D. candidate Qi Wei's thesis consists of two projects: Chemotherapy Project: a study based on the research paper "Predicting chemotherapy response of various cancer types using a variational auto-encoder approach" submitted to the bioRxiv preprint archive and accepted by the BMC bioinformatics; and Wound Monitor Project: implementing and assessing analytics...
Resource Type:: Dissertation
Full Text:: Assessment Abstract approved: Stephen A. Ramsey Ph.D. candidate Qi Wei’s thesis consists of two projects

Predicting Robotic Grasps Using Surrogate Datasets

Creator:: Unrath, Matthew Paul Nishita
Abstract:: One of the tasks that continues to prove difficult in robotics is the ability to grasp objects of varying shapes. It is time-consuming to acquire large amounts of real-world data in order to train accurate classifiers that can predict the success or failure of a grasp. To solve this issue,...
Resource Type:: Honors College Thesis
Full Text:: Using Surrogate Datasets by Matthew Paul Nishita Unrath A THESIS submitted to Oregon State

ScholarsArchive@OSU

A Security Analysis of the Signal Protocol’s Group Messaging Capabilities in Comparison to Direct Messaging

A collaborative filtering algorithm and evaluation metric that accurately model the user experience

A Study of Temporal Convolutional Neural Networks for Music Language Modeling as Applied to Automatic Music Transcription

Counterfactual States for Atari Agents via Generative Deep Learning

3D Voronoi Subdivision for Simulating Destructible and Granular Materials

Characterizing and Addressing Dataset Shift with Deep Learning

The Implementation of Passive RFID Tags to Sample Volumetric Water Content for an Autonomous Irrigation System

Analysis of Convolutional Neural Network Image Pre-processing Methods

Machine Learning for Precision Medicine: Application to Cancer Chemotherapy Response Prediction and Wound Healing Status Assessment

Predicting Robotic Grasps Using Surrogate Datasets

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